Aspects of the present invention relate to data mapping and translation maps to map data from one format to another format, and more particularly to translation map simplification.
Data mapping may be defined as a process for creating data element mappings or defining relationships between two distinct data models or formats for representing data. Data mapping may be used as a first step for a wide variety of data integration tasks. Examples of such data integration tasks may include but is not necessarily limited to data transformation or data mediation between a data source and a destination; identification of data relationships as part of data lineage analysis; the discovery of hidden sensitive data such as the last four digits of a social security number hidden in another user id as part of a data masking or de-identification project; and consolidation of multiple databases into a single database and identifying redundant columns of data for consolidation or elimination. For example, a company that would like to transmit and receive purchase orders and invoices with another company or a business partner may use data mapping to create data maps from a company's data to standardized American National Standards Institute Accredited Standards Committee X12 (ANSI ASC X12) messages or similar messages for items such as purchase orders and invoices. While standards may be generic, Electronic Data Interchange (EDI) standards are designed to allow a company to exchange data with any other company, regardless of industry.
Translation maps are used to map data from one format or data model to another format or data model. Companies may generate many custom maps based on data origin and subsequent use. Often these maps are similar, especially in business to business (B2B) scenarios where maps are based on standards, such as those discussed above, but partners may implement variations or may have specific content interpretations. These minor differences can cause a large number of translation maps to be created and maintained. Map reuse across partners is highly desirable but these mapping differences result in complexity and difficulties in translating the data from one company or partner to another.